Levels of Autonomy:
Command and Control of Hybrid Forces
Major Ricardo
Fernandes
Dr. Michael Hieb
Dr. Paulo Costa
Brazilian Army
George Mason
University
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Research Purpose
To define a Framework for
Command and Control of Hybrid Forces
using Cognitive Collaboration and Autonomy
involving Humans, Machines and Software
Entities in the same operational process.
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Hybrid Cognitive Collaboration
Collaboration is a process that produces
Actions to achieve a given set of Goals.
Cognitive Collaboration is the collaboration that
is restricted to the Cognitive Architecture, which
is presented below.
Hybrid means Humans and Machines in the
same process.
We use the
term HyCCo.
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Technology Trends
Increasing employment of Machines;
Human-Machine Collaboration;
Pressure for more Autonomy;
Large scale collaboration.
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Hybrid Military Operations
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Autonomy
Limits and Levels;
Initiative and Delegation;
Behavior control;
Problem solving needs.
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Autonomy Level for Unmanned Systems
(ALFUS)
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Autonomy Level for Unmanned Systems
(ALFUS)
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Non-Contextual Autonomy Potential
(NCAP)
Perception
(hardware)
Request
new data
Raw sensor data
Modeling
(software)
Internal
knowledge
update
state
Execution
(software/
hardware)
actions
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Planning
(software)
Non-Contextual Autonomy Potential
(NCAP)
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HyCCo
Cognitive Collaboration;
as a restriction of;
the general Collaboration problem.
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HyCCo
Cognitive Collaboration;
enables Hybrid Teams to handle;
the general Collaboration problem.
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Human
Sensing
Machine
Medium Glucose level;
Multi-dimensional;
Continuous Electric Power;
Low Latency;
Abstraction
High Glucose level;
Self-Organizing;
Continuous Electric Power;
Algorithmic;
Calculation
High Glucose level;
Estimation shortcuts;
Continuous Electric Power;
High Speed;
Medium Glucose level;
Self-Organizing;
Continuous Electric Power;
Algorithmic;
Pattern
discovery
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Cognitive
Agent
Architecture
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Cognitive Agent Architecture
Environmental
Stimulus
Action
Memory
Information
Perception
Information
Information
Reasoning
Information Processing
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Execution
Autonomy
In many dictionary definitions, associated with
freedom of self-government.
We consider self-government the ability to
preserve Goals by producing Responses to
environmental changes.
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Response Process
Goals: G
Response
Demand
Environment
Changes
Response
Production
A Demand for a
Response to
preserve G is
Identified
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Response
Selection
A List of
Candidate
Responses
Decision
Cognitive Agent Response
Environmental
Stimulus
Decision
Memory
Goal
Information
Perception
Information
Reasoning
Information Processing
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Selected
Response
Execution
Response Demand (Level 1)
Environmental
Stimulus
Response
Demand
Memory
Goal
Information
Perception
Information
Reasoning
Information Processing
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Response
Demand
Execution
Response Production (Level 2)
Response
Demand
Candidate
Responses
Memory
Response
Demand
Perception
Information
Goal
Information
Reasoning
Information Processing
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Candidate
Responses
Execution
Response Selection (Level 4)
Candidate
Responses
Decision
Memory
Candidate
Responses
Perception
Information
Goal
Information
Reasoning
Information Processing
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Selected
Response
Execution
Autonomy Levels: RD + 2*RP + 4*RS
0
1
2
3
Response
Demand
Response
Production
Response
Selection
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4
5
6
7
Experimentation
Validation of the Framework;
Validation of the Autonomy Levels;
Analysis of the Patterns of Interaction
which are correlated to the Autonomy
Levels configurations;
VR-Forces (MÄK).
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Conclusion
Developed a Framework for Collaboration
between Humans and Machines: HyCCo;
Created new Concepts for Autonomy
inspired by Cognition: Response Process;
Experimenting to determine validity of this
research: VR-Forces.
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